{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/nicolewu/Desktop/Automation/PSRM Replication/PSRM MB.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}21 Feb 2021, 18:05:48

{com}. use "/Users/nicolewu/Desktop/Automation/PSRM Replication/anes2016_cdata.dta"

. scatter auto_onetavg auto_fbavg, ysca(alt) xsca(alt) xlabel(, grid gmax) saving(main)
{res}{txt}(file main.gph saved)

{com}. twoway histogram auto_fbavg, density xsca(alt reverse) horiz xlabel(none) saving(y) fxsize(25)
{res}{txt}(file y.gph saved)

{com}. twoway histogram auto_onetavg, density ysca(alt reverse) ylabel(none, grid gmax) xlabel(, grid gmax) saving(x) fysize(25)              
{res}{txt}(file x.gph saved)

{com}. graph combine y.gph main.gph x.gph, hole(3) imargin(0 0 0 0) graphregion(margin(l=22 r=22))
{res}
{com}. 
. eststo: meologit immglevel auto_fbavg auto_onetavg if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2943.3347}  
Iteration 1:{space 3}log likelihood = {res: -2924.032}  
Iteration 2:{space 3}log likelihood = {res:-2924.0022}  
Iteration 3:{space 3}log likelihood = {res:-2924.0022}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3062.8874}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3062.8874}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2998.2189}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2965.8006}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-2953.0187}  (not concave)
Iteration 4:{space 3}log likelihood = {res:-2951.7483}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-2951.2405}  (not concave)
Iteration 6:{space 3}log likelihood = {res:-2951.0374}  (not concave)
Iteration 7:{space 3}log likelihood = {res:-2950.9967}  (not concave)
Iteration 8:{space 3}log likelihood = {res:-2950.9805}  (not concave)
Iteration 9:{space 3}log likelihood = {res:-2950.9789}  (not concave)
Iteration 10:{space 2}log likelihood = {res:-2950.9788}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-2950.9787}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-2950.9786}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-2950.9785}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-2950.9785}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-2950.9784}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-2950.9784}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-2950.9783}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2950.9782}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2950.9782}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-2950.9781}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2950.9781}  (not concave)
Iteration 22:{space 2}log likelihood = {res: -2950.978}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2950.9779}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2950.9779}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2950.9778}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2950.9778}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2950.9777}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2950.9777}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2950.9776}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2950.9775}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2950.9775}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2950.9774}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2950.9774}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2950.9773}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2950.9772}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2950.9772}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2950.9771}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2950.9771}  (not concave)
Iteration 39:{space 2}log likelihood = {res: -2950.977}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2950.9769}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2950.9769}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2950.9768}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2950.9768}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2950.9767}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2950.9766}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2950.9766}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2950.9765}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2950.9765}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2950.9764}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2950.9764}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-2950.9763}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-2950.9762}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-2950.9761}  (not concave)
Iteration 54:{space 2}log likelihood = {res: -2950.976}  (not concave)
Iteration 55:{space 2}log likelihood = {res:-2950.9759}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-2950.9755}  (not concave)
Iteration 57:{space 2}log likelihood = {res: -2950.974}  (not concave)
Iteration 58:{space 2}log likelihood = {res:-2950.9715}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-2950.9638}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-2950.9514}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-2950.9118}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-2950.8485}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-2950.4442}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-2949.1597}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-2945.1575}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-2942.0437}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-2941.8884}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-2941.8263}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-2941.8263}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-2941.8262}  (not concave)
Iteration 71:{space 2}log likelihood = {res:-2941.8262}  (not concave)
Iteration 72:{space 2}log likelihood = {res:-2941.8262}  (not concave)
Iteration 73:{space 2}log likelihood = {res:-2941.8261}  (not concave)
Iteration 74:{space 2}log likelihood = {res:-2941.8261}  (not concave)
Iteration 75:{space 2}log likelihood = {res:-2941.8261}  (not concave)
Iteration 76:{space 2}log likelihood = {res: -2941.826}  (not concave)
Iteration 77:{space 2}log likelihood = {res: -2941.826}  (not concave)
Iteration 78:{space 2}log likelihood = {res: -2941.826}  (not concave)
Iteration 79:{space 2}log likelihood = {res: -2941.826}  (not concave)
Iteration 80:{space 2}log likelihood = {res:-2941.8259}  (not concave)
Iteration 81:{space 2}log likelihood = {res:-2941.8259}  (not concave)
Iteration 82:{space 2}log likelihood = {res:-2941.8259}  (not concave)
Iteration 83:{space 2}log likelihood = {res:-2941.8258}  (not concave)
Iteration 84:{space 2}log likelihood = {res:-2941.8258}  (not concave)
Iteration 85:{space 2}log likelihood = {res:-2941.8258}  (not concave)
Iteration 86:{space 2}log likelihood = {res:-2941.8258}  (not concave)
Iteration 87:{space 2}log likelihood = {res:-2941.8257}  (not concave)
Iteration 88:{space 2}log likelihood = {res:-2941.8257}  (not concave)
Iteration 89:{space 2}log likelihood = {res:-2941.8257}  (not concave)
Iteration 90:{space 2}log likelihood = {res:-2941.8256}  (not concave)
Iteration 91:{space 2}log likelihood = {res:-2941.8256}  (not concave)
Iteration 92:{space 2}log likelihood = {res:-2941.8256}  (not concave)
Iteration 93:{space 2}log likelihood = {res:-2941.8255}  (not concave)
Iteration 94:{space 2}log likelihood = {res:-2941.8255}  (not concave)
Iteration 95:{space 2}log likelihood = {res:-2941.8255}  (not concave)
Iteration 96:{space 2}log likelihood = {res:-2941.8255}  (not concave)
Iteration 97:{space 2}log likelihood = {res:-2941.8254}  (not concave)
Iteration 98:{space 2}log likelihood = {res:-2941.8254}  (not concave)
Iteration 99:{space 2}log likelihood = {res:-2941.8253}  (not concave)
Iteration 100:{space 1}log likelihood = {res:-2941.8248}  (not concave)
Iteration 101:{space 1}log likelihood = {res:-2941.8246}  (not concave)
Iteration 102:{space 1}log likelihood = {res:-2941.8246}  (not concave)
Iteration 103:{space 1}log likelihood = {res:-2941.8241}  (not concave)
Iteration 104:{space 1}log likelihood = {res:-2941.8234}  (not concave)
Iteration 105:{space 1}log likelihood = {res: -2941.821}  (not concave)
Iteration 106:{space 1}log likelihood = {res:-2941.7901}  (not concave)
Iteration 107:{space 1}log likelihood = {res:-2941.7886}  (not concave)
Iteration 108:{space 1}log likelihood = {res:-2941.7837}  (not concave)
Iteration 109:{space 1}log likelihood = {res:-2941.7827}  (not concave)
Iteration 110:{space 1}log likelihood = {res:-2941.7322}  (not concave)
Iteration 111:{space 1}log likelihood = {res:-2936.8583}  (not concave)
Iteration 112:{space 1}log likelihood = {res:-2933.2076}  (not concave)
Iteration 113:{space 1}log likelihood = {res:-2931.7973}  (not concave)
Iteration 114:{space 1}log likelihood = {res: -2931.727}  (not concave)
Iteration 115:{space 1}log likelihood = {res:-2931.2822}  (not concave)
Iteration 116:{space 1}log likelihood = {res:-2929.9178}  (not concave)
Iteration 117:{space 1}log likelihood = {res: -2928.869}  (not concave)
Iteration 118:{space 1}log likelihood = {res:-2928.6612}  (not concave)
Iteration 119:{space 1}log likelihood = {res:-2928.6197}  (not concave)
Iteration 120:{space 1}log likelihood = {res:-2926.7014}  (not concave)
Iteration 121:{space 1}log likelihood = {res:-2923.4683}  
Iteration 122:{space 1}log likelihood = {res:-2923.3764}  
Iteration 123:{space 1}log likelihood = {res:-2922.5618}  (not concave)
Iteration 124:{space 1}log likelihood = {res:-2922.5568}  
Iteration 125:{space 1}log likelihood = {res:-2922.5128}  (not concave)
Iteration 126:{space 1}log likelihood = {res:-2922.5042}  
Iteration 127:{space 1}log likelihood = {res:-2922.4853}  (not concave)
Iteration 128:{space 1}log likelihood = {res:-2922.4834}  
Iteration 129:{space 1}log likelihood = {res:-2922.2503}  (not concave)
Iteration 130:{space 1}log likelihood = {res:-2922.2503}  (not concave)
Iteration 131:{space 1}log likelihood = {res:-2922.2503}  (not concave)
Iteration 132:{space 1}log likelihood = {res:-2922.2503}  (not concave)
Iteration 133:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 134:{space 1}log likelihood = {res:-2922.2497}  (backed up)
Iteration 135:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 136:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 137:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 138:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 139:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 140:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 141:{space 1}log likelihood = {res:-2922.2497}  (not concave)
Iteration 142:{space 1}log likelihood = {res:-2922.2496}  (not concave)
Iteration 143:{space 1}log likelihood = {res:-2922.2496}  (not concave)
Iteration 144:{space 1}log likelihood = {res:-2922.2496}  (not concave)
Iteration 145:{space 1}log likelihood = {res:-2922.2496}  (not concave)
Iteration 146:{space 1}log likelihood = {res:-2922.2496}  (backed up)
Iteration 147:{space 1}log likelihood = {res:-2922.2433}  (not concave)
Iteration 148:{space 1}log likelihood = {res:-2922.2433}  (not concave)
Iteration 149:{space 1}log likelihood = {res:-2922.2433}  (not concave)
Iteration 150:{space 1}log likelihood = {res:-2922.2433}  (not concave)
Iteration 151:{space 1}log likelihood = {res:-2922.2433}  (not concave)
Iteration 152:{space 1}log likelihood = {res:-2922.2433}  
Iteration 153:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 154:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 155:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 156:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 157:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 158:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 159:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 160:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 161:{space 1}log likelihood = {res:-2922.2429}  (not concave)
Iteration 162:{space 1}log likelihood = {res:-2922.2429}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     2,073

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     457{col 31}        1{col 42}      4.5{col 53}       59
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,139{col 31}        1{col 42}      1.8{col 53}       58
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   2,053{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 67}={res}{col 70}    18.90
{txt}Log likelihood = {res}-2922.2429{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0001
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              immglevel{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2}  .824547{col 37}{space 2}  .199134{col 48}{space 1}    4.14{col 57}{space 3}0.000{col 65}{space 4} .4342515{col 78}{space 3} 1.214842
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2}  .465672{col 37}{space 2} .4598879{col 48}{space 1}    1.01{col 57}{space 3}0.311{col 65}{space 4}-.4356917{col 78}{space 3} 1.367036
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-3.064779{col 37}{space 2} .5362799{col 65}{space 4}-4.115868{col 78}{space 3} -2.01369
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2}-1.633093{col 37}{space 2} .3411264{col 65}{space 4}-2.301689{col 78}{space 3}-.9644976
{txt}{space 18}/cut3 {c |}{col 25}{res}{space 2}  1.04164{col 37}{space 2} .2337425{col 65}{space 4} .5835132{col 78}{space 3} 1.499767
{txt}{space 18}/cut4 {c |}{col 25}{res}{space 2}  2.28119{col 37}{space 2} .4278044{col 65}{space 4} 1.442709{col 78}{space 3} 3.119672
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 3.08e-45{col 37}{space 2} 2.26e-26{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 6.21e-43{col 37}{space 2} 1.20e-24{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 1.968085{col 37}{space 2} 1.661504{col 65}{space 4} .3762178{col 78}{space 3} 10.29552
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 3.52{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0303
{txt}({res}est5{txt} stored)

{com}. eststo: meologit immglevel auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2565.6104}  
Iteration 1:{space 3}log likelihood = {res:-2315.9605}  
Iteration 2:{space 3}log likelihood = {res:-2308.9667}  
Iteration 3:{space 3}log likelihood = {res:-2308.9467}  
Iteration 4:{space 3}log likelihood = {res:-2308.9467}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2437.2713}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2437.2713}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2386.3838}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2360.3478}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-2337.8981}  (not concave)
Iteration 4:{space 3}log likelihood = {res:-2333.3729}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-2331.5561}  (not concave)
Iteration 6:{space 3}log likelihood = {res:-2330.8288}  (not concave)
Iteration 7:{space 3}log likelihood = {res: -2330.756}  (not concave)
Iteration 8:{space 3}log likelihood = {res:-2330.7488}  (not concave)
Iteration 9:{space 3}log likelihood = {res: -2330.748}  (not concave)
Iteration 10:{space 2}log likelihood = {res:-2330.7478}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-2330.7477}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-2330.7477}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2330.7476}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2330.7475}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2330.7475}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2330.7475}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2330.7475}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2330.7475}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2330.7468}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2330.7372}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2330.7334}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2330.7303}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2330.7254}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2330.7253}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2330.6776}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2330.0686}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2330.0533}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2329.2771}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2328.0434}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2327.9817}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2327.9324}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2327.9275}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2327.9273}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2327.9272}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2327.9271}  (not concave)
Iteration 51:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 52:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 53:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 54:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 55:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 56:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 57:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 58:{space 2}log likelihood = {res: -2327.927}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-2327.9269}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 71:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 72:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 73:{space 2}log likelihood = {res:-2327.9268}  (not concave)
Iteration 74:{space 2}log likelihood = {res:-2327.9266}  (not concave)
Iteration 75:{space 2}log likelihood = {res:-2327.9262}  (not concave)
Iteration 76:{space 2}log likelihood = {res:-2327.9261}  (not concave)
Iteration 77:{space 2}log likelihood = {res:-2327.9201}  (not concave)
Iteration 78:{space 2}log likelihood = {res:-2327.9195}  (not concave)
Iteration 79:{space 2}log likelihood = {res:-2327.9194}  (not concave)
Iteration 80:{space 2}log likelihood = {res:-2327.9135}  (not concave)
Iteration 81:{space 2}log likelihood = {res:-2327.9039}  (not concave)
Iteration 82:{space 2}log likelihood = {res:-2327.8963}  (not concave)
Iteration 83:{space 2}log likelihood = {res:-2327.5073}  (not concave)
Iteration 84:{space 2}log likelihood = {res:-2327.3519}  (not concave)
Iteration 85:{space 2}log likelihood = {res:-2327.2278}  (not concave)
Iteration 86:{space 2}log likelihood = {res:-2327.0296}  (not concave)
Iteration 87:{space 2}log likelihood = {res:-2326.8713}  (not concave)
Iteration 88:{space 2}log likelihood = {res:-2326.3673}  (not concave)
Iteration 89:{space 2}log likelihood = {res:-2326.3169}  (not concave)
Iteration 90:{space 2}log likelihood = {res:-2326.1561}  (not concave)
Iteration 91:{space 2}log likelihood = {res:-2325.6441}  (not concave)
Iteration 92:{space 2}log likelihood = {res:-2325.5419}  (not concave)
Iteration 93:{space 2}log likelihood = {res:-2310.5065}  (not concave)
Iteration 94:{space 2}log likelihood = {res:-2310.5007}  (not concave)
Iteration 95:{space 2}log likelihood = {res:-2310.4636}  (not concave)
Iteration 96:{space 2}log likelihood = {res: -2310.434}  (not concave)
Iteration 97:{space 2}log likelihood = {res:-2310.3871}  (not concave)
Iteration 98:{space 2}log likelihood = {res:-2310.1006}  (not concave)
Iteration 99:{space 2}log likelihood = {res:-2310.0721}  (not concave)
Iteration 100:{space 1}log likelihood = {res:-2310.0494}  (not concave)
Iteration 101:{space 1}log likelihood = {res:-2310.0449}  
Iteration 102:{space 1}log likelihood = {res:-2309.0951}  
Iteration 103:{space 1}log likelihood = {res:-2309.0555}  
Iteration 104:{space 1}log likelihood = {res:-2308.9878}  (not concave)
Iteration 105:{space 1}log likelihood = {res:-2308.8499}  (not concave)
Iteration 106:{space 1}log likelihood = {res:-2308.8498}  (not concave)
Iteration 107:{space 1}log likelihood = {res:-2308.8497}  
Iteration 108:{space 1}log likelihood = {res:-2308.8302}  (not concave)
Iteration 109:{space 1}log likelihood = {res:  -2308.83}  (not concave)
Iteration 110:{space 1}log likelihood = {res:-2308.8175}  
Iteration 111:{space 1}log likelihood = {res:-2308.8114}  (not concave)
Iteration 112:{space 1}log likelihood = {res:-2308.8114}  (backed up)
Iteration 113:{space 1}log likelihood = {res:-2308.8009}  
Iteration 114:{space 1}log likelihood = {res:-2308.7854}  
Iteration 115:{space 1}log likelihood = {res:-2308.7841}  
Iteration 116:{space 1}log likelihood = {res:-2308.7628}  (not concave)
Iteration 117:{space 1}log likelihood = {res:-2308.7628}  (not concave)
Iteration 118:{space 1}log likelihood = {res:-2308.7628}  
Iteration 119:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 120:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 121:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 122:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 123:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 124:{space 1}log likelihood = {res:-2308.7627}  
Iteration 125:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 126:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 127:{space 1}log likelihood = {res:-2308.7627}  
Iteration 128:{space 1}log likelihood = {res:-2308.7627}  (not concave)
Iteration 129:{space 1}log likelihood = {res:-2308.7627}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     1,811

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     433{col 31}        1{col 42}      4.2{col 53}       53
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,031{col 31}        1{col 42}      1.8{col 53}       53
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   1,793{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}   122.30
{txt}Log likelihood = {res}-2308.7627{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              immglevel{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2} .4585124{col 37}{space 2} .1456344{col 48}{space 1}    3.15{col 57}{space 3}0.002{col 65}{space 4} .1730742{col 78}{space 3} .7439506
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2} .1823578{col 37}{space 2} .4336752{col 48}{space 1}    0.42{col 57}{space 3}0.674{col 65}{space 4}  -.66763{col 78}{space 3} 1.032346
{txt}{space 11}offshore_avg {c |}{col 25}{res}{space 2}  .012167{col 37}{space 2} .0382799{col 48}{space 1}    0.32{col 57}{space 3}0.751{col 65}{space 4}-.0628603{col 78}{space 3} .0871943
{txt}{space 13}imppen2012 {c |}{col 25}{res}{space 2}-.1574034{col 37}{space 2} .1835401{col 48}{space 1}   -0.86{col 57}{space 3}0.391{col 65}{space 4}-.5171353{col 78}{space 3} .2023286
{txt}{space 10}foreignbornpc {c |}{col 25}{res}{space 2}-.0188113{col 37}{space 2} .0049934{col 48}{space 1}   -3.77{col 57}{space 3}0.000{col 65}{space 4}-.0285981{col 78}{space 3}-.0090245
{txt}{space 17}gender {c |}{col 25}{res}{space 2}-.2243849{col 37}{space 2} .0962526{col 48}{space 1}   -2.33{col 57}{space 3}0.020{col 65}{space 4}-.4130366{col 78}{space 3}-.0357333
{txt}{space 16}partyid {c |}{col 25}{res}{space 2} .3016257{col 37}{space 2}  .034292{col 48}{space 1}    8.80{col 57}{space 3}0.000{col 65}{space 4} .2344146{col 78}{space 3} .3688367
{txt}{space 20}age {c |}{col 25}{res}{space 2}  .015214{col 37}{space 2} .0036623{col 48}{space 1}    4.15{col 57}{space 3}0.000{col 65}{space 4} .0080359{col 78}{space 3}  .022392
{txt}{space 20}edu {c |}{col 25}{res}{space 2}-.0814342{col 37}{space 2} .0251322{col 48}{space 1}   -3.24{col 57}{space 3}0.001{col 65}{space 4}-.1306923{col 78}{space 3} -.032176
{txt}{space 12}nationalism {c |}{col 25}{res}{space 2}  .257184{col 37}{space 2} .0482444{col 48}{space 1}    5.33{col 57}{space 3}0.000{col 65}{space 4} .1626267{col 78}{space 3} .3517413
{txt}{space 8}ethnocentric100 {c |}{col 25}{res}{space 2} 2.635831{col 37}{space 2} .3351622{col 48}{space 1}    7.86{col 57}{space 3}0.000{col 65}{space 4} 1.978925{col 78}{space 3} 3.292737
{txt}{space 14}famincome {c |}{col 25}{res}{space 2} .0080259{col 37}{space 2} .0068974{col 48}{space 1}    1.16{col 57}{space 3}0.245{col 65}{space 4}-.0054928{col 78}{space 3} .0215446
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-1.815905{col 37}{space 2} .3731808{col 65}{space 4}-2.547326{col 78}{space 3}-1.084484
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2}-.4390201{col 37}{space 2} .3501763{col 65}{space 4}-1.125353{col 78}{space 3} .2473129
{txt}{space 18}/cut3 {c |}{col 25}{res}{space 2} 2.080603{col 37}{space 2} .4002928{col 65}{space 4} 1.296043{col 78}{space 3} 2.865162
{txt}{space 18}/cut4 {c |}{col 25}{res}{space 2} 3.237637{col 37}{space 2} .4594338{col 65}{space 4} 2.337164{col 78}{space 3} 4.138111
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 1.00e-42{col 37}{space 2} 3.63e-24{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 3.74e-38{col 37}{space 2} 1.36e-20{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .2589277{col 37}{space 2} .4817123{col 65}{space 4} .0067545{col 78}{space 3} 9.925779
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 0.37{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.2721
{txt}({res}est6{txt} stored)

{com}. eststo: meologit opposetrade auto_fbavg auto_onetavg if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-3382.2073}  
Iteration 1:{space 3}log likelihood = {res:-3358.8079}  
Iteration 2:{space 3}log likelihood = {res:-3358.7629}  
Iteration 3:{space 3}log likelihood = {res:-3358.7629}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3498.1315}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3498.1315}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-3426.2237}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-3421.8903}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-3420.1509}  (not concave)
Iteration 4:{space 3}log likelihood = {res: -3418.756}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-3418.4769}  (not concave)
Iteration 6:{space 3}log likelihood = {res:-3418.4211}  (not concave)
Iteration 7:{space 3}log likelihood = {res:-3418.4204}  (not concave)
Iteration 8:{space 3}log likelihood = {res:-3418.4193}  (not concave)
Iteration 9:{space 3}log likelihood = {res:-3418.4184}  (not concave)
Iteration 10:{space 2}log likelihood = {res: -3418.417}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-3418.4164}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-3418.4159}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-3418.4152}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-3418.4146}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-3418.4141}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-3418.4134}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-3418.4128}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-3418.4123}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-3418.4116}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-3418.4109}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-3418.4104}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-3418.4097}  (not concave)
Iteration 23:{space 2}log likelihood = {res: -3418.409}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-3418.4085}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-3418.4077}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-3418.4071}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-3418.4066}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-3418.4057}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-3418.4051}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-3418.4046}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-3418.4037}  (not concave)
Iteration 32:{space 2}log likelihood = {res: -3418.403}  (not concave)
Iteration 33:{space 2}log likelihood = {res: -3418.402}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-3418.4002}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-3418.3781}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-3418.3693}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-3418.3684}  (not concave)
Iteration 38:{space 2}log likelihood = {res: -3418.367}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-3418.3624}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-3417.4325}  (not concave)
Iteration 41:{space 2}log likelihood = {res: -3415.939}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-3415.7896}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-3415.7822}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-3415.5909}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-3413.1317}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-3397.2128}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -3385.172}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-3359.8177}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-3358.1617}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-3358.1413}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-3358.1094}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-3357.8158}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-3357.7886}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-3357.7782}  (not concave)
Iteration 55:{space 2}log likelihood = {res: -3357.774}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-3357.7708}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-3357.7705}  (not concave)
Iteration 58:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-3357.7704}  (backed up)
Iteration 71:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 72:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 73:{space 2}log likelihood = {res:-3357.7704}  (backed up)
Iteration 74:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 75:{space 2}log likelihood = {res:-3357.7704}  (backed up)
Iteration 76:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 77:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 78:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 79:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 80:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 81:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 82:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 83:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 84:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 85:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 86:{space 2}log likelihood = {res:-3357.7704}  (not concave)
Iteration 87:{space 2}log likelihood = {res:-3357.7704}  (backed up)
Iteration 88:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 89:{space 2}log likelihood = {res:-3357.3283}  (backed up)
Iteration 90:{space 2}log likelihood = {res:-3357.3283}  (backed up)
Iteration 91:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 92:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 93:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 94:{space 2}log likelihood = {res:-3357.3283}  (backed up)
Iteration 95:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 96:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 97:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 98:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 99:{space 2}log likelihood = {res:-3357.3283}  (not concave)
Iteration 100:{space 1}log likelihood = {res:-3357.3283}  (not concave)
Iteration 101:{space 1}log likelihood = {res:-3357.3282}  (not concave)
Iteration 102:{space 1}log likelihood = {res:-3357.3282}  
Iteration 103:{space 1}log likelihood = {res:-3357.3229}  (not concave)
Iteration 104:{space 1}log likelihood = {res:-3357.3229}  (not concave)
Iteration 105:{space 1}log likelihood = {res:-3357.3229}  (not concave)
Iteration 106:{space 1}log likelihood = {res:-3357.3229}  (not concave)
Iteration 107:{space 1}log likelihood = {res:-3357.3229}  (not concave)
Iteration 108:{space 1}log likelihood = {res:-3357.3229}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     2,059

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     457{col 31}        1{col 42}      4.5{col 53}       59
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,132{col 31}        1{col 42}      1.8{col 53}       55
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   2,040{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 67}={res}{col 70}    40.53
{txt}Log likelihood = {res}-3357.3229{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            opposetrade{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2} .7460242{col 37}{space 2} .1242135{col 48}{space 1}    6.01{col 57}{space 3}0.000{col 65}{space 4} .5025702{col 78}{space 3} .9894781
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2}-1.336532{col 37}{space 2} .3808337{col 48}{space 1}   -3.51{col 57}{space 3}0.000{col 65}{space 4}-2.082952{col 78}{space 3}-.5901116
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-2.349963{col 37}{space 2} .1455165{col 65}{space 4} -2.63517{col 78}{space 3}-2.064756
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2}-.8230963{col 37}{space 2} .1289491{col 65}{space 4}-1.075832{col 78}{space 3}-.5703607
{txt}{space 18}/cut3 {c |}{col 25}{res}{space 2}-.4758962{col 37}{space 2} .1273803{col 65}{space 4} -.725557{col 78}{space 3}-.2262354
{txt}{space 18}/cut4 {c |}{col 25}{res}{space 2} 1.446631{col 37}{space 2} .1326172{col 65}{space 4} 1.186706{col 78}{space 3} 1.706555
{txt}{space 18}/cut5 {c |}{col 25}{res}{space 2} 1.750909{col 37}{space 2} .1356921{col 65}{space 4} 1.484957{col 78}{space 3} 2.016861
{txt}{space 18}/cut6 {c |}{col 25}{res}{space 2} 2.821839{col 37}{space 2} .1545509{col 65}{space 4} 2.518925{col 78}{space 3} 3.124753
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .0238366{col 37}{space 2} .0466226{col 65}{space 4} .0005157{col 78}{space 3} 1.101867
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .0863288{col 37}{space 2}  .103255{col 65}{space 4} .0082806{col 78}{space 3} .9000157
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 7.25e-33{col 37}{space 2} 1.18e-17{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}chi2({res}2{txt}) ={res} 2.88{col 59}{txt}Prob > chi2 ={res}{col 73}0.2369

{txt}{p 0 6 4 79}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}
({res}est7{txt} stored)

{com}. eststo: meologit opposetrade auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2961.0799}  
Iteration 1:{space 3}log likelihood = {res:-2889.0847}  
Iteration 2:{space 3}log likelihood = {res:-2888.4975}  
Iteration 3:{space 3}log likelihood = {res:-2888.4973}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3012.4284}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3012.4284}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2981.8281}  (not concave)
Iteration 2:{space 3}log likelihood = {res: -2950.129}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-2937.2845}  (not concave)
Iteration 4:{space 3}log likelihood = {res:-2932.1671}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-2928.1155}  (not concave)
Iteration 6:{space 3}log likelihood = {res:  -2921.77}  (not concave)
Iteration 7:{space 3}log likelihood = {res:-2919.2641}  (not concave)
Iteration 8:{space 3}log likelihood = {res: -2919.139}  (not concave)
Iteration 9:{space 3}log likelihood = {res:-2919.0889}  (not concave)
Iteration 10:{space 2}log likelihood = {res:-2919.0689}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-2919.0649}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-2919.0633}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-2919.0632}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-2919.0632}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-2919.0632}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-2919.0631}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-2919.0631}  (not concave)
Iteration 18:{space 2}log likelihood = {res: -2919.063}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2919.0629}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-2919.0629}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2919.0628}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2919.0628}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2919.0627}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2919.0627}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2919.0626}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2919.0625}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2919.0625}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2919.0624}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2919.0624}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2919.0624}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2919.0623}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2919.0623}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2919.0621}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2919.0583}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2919.0524}  (not concave)
Iteration 36:{space 2}log likelihood = {res:  -2919.05}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2919.0481}  (not concave)
Iteration 38:{space 2}log likelihood = {res: -2919.045}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2918.9667}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2918.9657}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2918.1668}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2917.5298}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2917.4026}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2916.9962}  (not concave)
Iteration 45:{space 2}log likelihood = {res: -2911.945}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2910.9437}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -2891.854}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2891.7364}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2891.5507}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2891.4769}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-2889.8609}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-2888.8176}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-2888.8167}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-2888.2967}  (not concave)
Iteration 55:{space 2}log likelihood = {res:-2888.2902}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-2888.2123}  (not concave)
Iteration 57:{space 2}log likelihood = {res: -2888.182}  (not concave)
Iteration 58:{space 2}log likelihood = {res:-2888.1759}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-2888.1758}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-2888.1721}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-2888.1706}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-2888.1703}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 71:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 72:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 73:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 74:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 75:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 76:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 77:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 78:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 79:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 80:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 81:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 82:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 83:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 84:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 85:{space 2}log likelihood = {res:-2888.1702}  (backed up)
Iteration 86:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 87:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 88:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 89:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 90:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 91:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 92:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 93:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 94:{space 2}log likelihood = {res:-2888.1702}  (not concave)
Iteration 95:{space 2}log likelihood = {res:-2888.1701}  (not concave)
Iteration 96:{space 2}log likelihood = {res:-2888.1701}  (not concave)
Iteration 97:{space 2}log likelihood = {res:-2888.1701}  (not concave)
Iteration 98:{space 2}log likelihood = {res:  -2888.17}  (not concave)
Iteration 99:{space 2}log likelihood = {res:-2888.1697}  
Iteration 100:{space 1}log likelihood = {res:-2888.1469}  (not concave)
Iteration 101:{space 1}log likelihood = {res:-2888.1463}  (not concave)
Iteration 102:{space 1}log likelihood = {res:-2888.1461}  (not concave)
Iteration 103:{space 1}log likelihood = {res:-2888.1456}  
Iteration 104:{space 1}log likelihood = {res:-2888.0897}  (not concave)
Iteration 105:{space 1}log likelihood = {res:-2888.0871}  (not concave)
Iteration 106:{space 1}log likelihood = {res: -2888.087}  (not concave)
Iteration 107:{space 1}log likelihood = {res:-2888.0787}  (not concave)
Iteration 108:{space 1}log likelihood = {res:-2888.0783}  (not concave)
Iteration 109:{space 1}log likelihood = {res:-2888.0783}  
Iteration 110:{space 1}log likelihood = {res:-2888.0693}  (not concave)
Iteration 111:{space 1}log likelihood = {res:-2888.0693}  (not concave)
Iteration 112:{space 1}log likelihood = {res:-2888.0693}  (not concave)
Iteration 113:{space 1}log likelihood = {res:-2888.0693}  (not concave)
Iteration 114:{space 1}log likelihood = {res:-2888.0693}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     1,801

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     433{col 31}        1{col 42}      4.2{col 53}       50
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,027{col 31}        1{col 42}      1.8{col 53}       50
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   1,784{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}   132.26
{txt}Log likelihood = {res}-2888.0693{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            opposetrade{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2} .3189907{col 37}{space 2} .1397726{col 48}{space 1}    2.28{col 57}{space 3}0.022{col 65}{space 4} .0450413{col 78}{space 3} .5929401
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2}-.8890155{col 37}{space 2} .4288961{col 48}{space 1}   -2.07{col 57}{space 3}0.038{col 65}{space 4}-1.729636{col 78}{space 3}-.0483947
{txt}{space 11}offshore_avg {c |}{col 25}{res}{space 2} .0545128{col 37}{space 2} .0374103{col 48}{space 1}    1.46{col 57}{space 3}0.145{col 65}{space 4}  -.01881{col 78}{space 3} .1278356
{txt}{space 13}imppen2012 {c |}{col 25}{res}{space 2}-.2620595{col 37}{space 2}  .193089{col 48}{space 1}   -1.36{col 57}{space 3}0.175{col 65}{space 4}-.6405069{col 78}{space 3} .1163879
{txt}{space 10}foreignbornpc {c |}{col 25}{res}{space 2}-.0137385{col 37}{space 2} .0044912{col 48}{space 1}   -3.06{col 57}{space 3}0.002{col 65}{space 4} -.022541{col 78}{space 3} -.004936
{txt}{space 17}gender {c |}{col 25}{res}{space 2}-.2523263{col 37}{space 2} .0911497{col 48}{space 1}   -2.77{col 57}{space 3}0.006{col 65}{space 4}-.4309765{col 78}{space 3}-.0736761
{txt}{space 16}partyid {c |}{col 25}{res}{space 2} .1206618{col 37}{space 2}   .02232{col 48}{space 1}    5.41{col 57}{space 3}0.000{col 65}{space 4} .0769154{col 78}{space 3} .1644083
{txt}{space 20}age {c |}{col 25}{res}{space 2}-.0070537{col 37}{space 2} .0032395{col 48}{space 1}   -2.18{col 57}{space 3}0.029{col 65}{space 4} -.013403{col 78}{space 3}-.0007043
{txt}{space 20}edu {c |}{col 25}{res}{space 2}-.1353286{col 37}{space 2} .0238955{col 48}{space 1}   -5.66{col 57}{space 3}0.000{col 65}{space 4}-.1821629{col 78}{space 3}-.0884943
{txt}{space 12}nationalism {c |}{col 25}{res}{space 2} .0304258{col 37}{space 2} .0414932{col 48}{space 1}    0.73{col 57}{space 3}0.463{col 65}{space 4}-.0508993{col 78}{space 3} .1117509
{txt}{space 8}ethnocentric100 {c |}{col 25}{res}{space 2}   .36975{col 37}{space 2} .2466866{col 48}{space 1}    1.50{col 57}{space 3}0.134{col 65}{space 4}-.1137469{col 78}{space 3} .8532468
{txt}{space 14}famincome {c |}{col 25}{res}{space 2}-.0020229{col 37}{space 2} .0065647{col 48}{space 1}   -0.31{col 57}{space 3}0.758{col 65}{space 4}-.0148896{col 78}{space 3} .0108437
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-4.082312{col 37}{space 2} .3527135{col 65}{space 4}-4.773618{col 78}{space 3}-3.391006
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2}-2.454334{col 37}{space 2} .3400207{col 65}{space 4}-3.120762{col 78}{space 3}-1.787906
{txt}{space 18}/cut3 {c |}{col 25}{res}{space 2}-2.079869{col 37}{space 2} .3380909{col 65}{space 4}-2.742515{col 78}{space 3}-1.417223
{txt}{space 18}/cut4 {c |}{col 25}{res}{space 2}-.1012964{col 37}{space 2}  .335996{col 65}{space 4}-.7598364{col 78}{space 3} .5572436
{txt}{space 18}/cut5 {c |}{col 25}{res}{space 2} .2076245{col 37}{space 2} .3374704{col 65}{space 4}-.4538053{col 78}{space 3} .8690543
{txt}{space 18}/cut6 {c |}{col 25}{res}{space 2} 1.266883{col 37}{space 2} .3468726{col 65}{space 4} .5870252{col 78}{space 3} 1.946741
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 1.01e-34{col 37}{space 2} 3.44e-18{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .0934978{col 37}{space 2} .1072411{col 65}{space 4} .0098737{col 78}{space 3} .8853641
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 2.83e-33{col 37}{space 2} 6.62e-18{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 0.86{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.1774
{txt}({res}est8{txt} stored)

{com}. eststo: meologit outsource auto_fbavg auto_onetavg if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-1523.1965}  
Iteration 1:{space 3}log likelihood = {res:-1521.4604}  
Iteration 2:{space 3}log likelihood = {res:-1521.4597}  
Iteration 3:{space 3}log likelihood = {res:-1521.4597}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-1567.0035}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-1567.0035}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-1552.2008}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-1536.9162}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-1525.8961}  (not concave)
Iteration 4:{space 3}log likelihood = {res:-1522.1346}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-1520.8031}  (not concave)
Iteration 6:{space 3}log likelihood = {res:-1520.3077}  (not concave)
Iteration 7:{space 3}log likelihood = {res:-1520.2104}  (not concave)
Iteration 8:{space 3}log likelihood = {res:-1520.1337}  (not concave)
Iteration 9:{space 3}log likelihood = {res:-1520.1261}  (not concave)
Iteration 10:{space 2}log likelihood = {res: -1520.123}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-1520.1218}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-1520.1208}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-1520.1207}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-1520.1206}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-1520.1205}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-1520.1196}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-1520.1195}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-1520.1195}  (not concave)
Iteration 55:{space 2}log likelihood = {res: -1520.119}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-1520.1159}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-1520.1134}  
Iteration 58:{space 2}log likelihood = {res:-1519.4469}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-1519.4449}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-1519.3935}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-1519.3733}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-1519.3652}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-1519.0429}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-1519.0124}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-1518.9893}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-1518.9716}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-1518.8576}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-1518.8572}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-1518.8562}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-1518.8553}  
Iteration 71:{space 2}log likelihood = {res: -1518.794}  (not concave)
Iteration 72:{space 2}log likelihood = {res: -1518.791}  (not concave)
Iteration 73:{space 2}log likelihood = {res:-1518.6732}  (not concave)
Iteration 74:{space 2}log likelihood = {res:-1518.6728}  (not concave)
Iteration 75:{space 2}log likelihood = {res:-1518.6722}  (not concave)
Iteration 76:{space 2}log likelihood = {res:-1518.6598}  (not concave)
Iteration 77:{space 2}log likelihood = {res:-1518.6595}  (not concave)
Iteration 78:{space 2}log likelihood = {res:-1518.6566}  (not concave)
Iteration 79:{space 2}log likelihood = {res:-1518.6566}  
Iteration 80:{space 2}log likelihood = {res:-1518.6527}  
Iteration 81:{space 2}log likelihood = {res:-1518.6468}  (not concave)
Iteration 82:{space 2}log likelihood = {res:-1518.6468}  (backed up)
Iteration 83:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 84:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 85:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 86:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 87:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 88:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 89:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 90:{space 2}log likelihood = {res:-1518.6467}  (not concave)
Iteration 91:{space 2}log likelihood = {res:-1518.6467}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     2,076

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     458{col 31}        1{col 42}      4.5{col 53}       59
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,142{col 31}        1{col 42}      1.8{col 53}       58
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   2,056{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 67}={res}{col 70}     2.64
{txt}Log likelihood = {res}-1518.6467{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.2671
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              outsource{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2} .0599783{col 37}{space 2}  .180137{col 48}{space 1}    0.33{col 57}{space 3}0.739{col 65}{space 4}-.2930838{col 78}{space 3} .4130403
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2} .8317948{col 37}{space 2} .5774909{col 48}{space 1}    1.44{col 57}{space 3}0.150{col 65}{space 4}-.3000667{col 78}{space 3} 1.963656
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-3.369174{col 37}{space 2} .6833294{col 65}{space 4}-4.708475{col 78}{space 3}-2.029873
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2}-.7518438{col 37}{space 2} .2692715{col 65}{space 4}-1.279606{col 78}{space 3}-.2240814
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .1691007{col 37}{space 2} .1221844{col 65}{space 4} .0410305{col 78}{space 3} .6969223
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 3.06e-32{col 37}{space 2} 5.38e-17{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 1.048157{col 37}{space 2} 1.629577{col 65}{space 4} .0497803{col 78}{space 3} 22.06964
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}chi2({res}2{txt}) ={res} 5.63{col 59}{txt}Prob > chi2 ={res}{col 73}0.0600

{txt}{p 0 6 4 79}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}
({res}est9{txt} stored)

{com}. eststo: meologit outsource auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 || cc_onet: || industry: || cd_merge: 
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-1334.3362}  
Iteration 1:{space 3}log likelihood = {res: -1314.483}  
Iteration 2:{space 3}log likelihood = {res:-1314.3647}  
Iteration 3:{space 3}log likelihood = {res:-1314.3647}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-1356.7095}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-1356.7095}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-1343.0773}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-1329.8259}  (not concave)
Iteration 3:{space 3}log likelihood = {res:-1319.8919}  (not concave)
Iteration 4:{space 3}log likelihood = {res:-1318.9325}  (not concave)
Iteration 5:{space 3}log likelihood = {res:-1318.8369}  (not concave)
Iteration 6:{space 3}log likelihood = {res:-1318.7987}  (not concave)
Iteration 7:{space 3}log likelihood = {res:-1318.7986}  (not concave)
Iteration 8:{space 3}log likelihood = {res:-1318.7986}  (not concave)
Iteration 9:{space 3}log likelihood = {res:-1318.7986}  (not concave)
Iteration 10:{space 2}log likelihood = {res:-1318.7986}  (not concave)
Iteration 11:{space 2}log likelihood = {res:-1318.7986}  (not concave)
Iteration 12:{space 2}log likelihood = {res:-1318.7986}  (not concave)
Iteration 13:{space 2}log likelihood = {res:-1318.7986}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-1318.7986}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-1318.7985}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-1318.7984}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-1318.7983}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-1318.7982}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-1318.7982}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-1318.7982}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-1318.7982}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-1318.7981}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-1318.7977}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-1318.7975}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-1318.7965}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-1318.7947}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-1318.7933}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-1318.7932}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-1318.7861}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-1318.6063}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-1318.5973}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-1318.4827}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-1318.3915}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-1313.3363}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-1313.3285}  (backed up)
Iteration 55:{space 2}log likelihood = {res:-1312.9333}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-1312.9333}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-1312.9309}  (not concave)
Iteration 58:{space 2}log likelihood = {res:-1312.9309}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-1312.9309}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-1312.9309}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-1312.9287}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-1312.9287}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-1312.9287}  
Iteration 64:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-1312.9232}  (backed up)
Iteration 67:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 68:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 69:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 70:{space 2}log likelihood = {res:-1312.9232}  (not concave)
Iteration 71:{space 2}log likelihood = {res:-1312.9232}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}     1,814

{txt}{hline 16}{c TT}{hline 44}
{col 17}{txt}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}{txt}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{txt}{hline 16}{c +}{hline 44}
{col 9}{res}cc_onet{col 17}{txt}{c |}{res}{col 21}     434{col 31}        1{col 42}      4.2{col 53}       53
{col 8}{res}industry{col 17}{txt}{c |}{res}{col 21}   1,033{col 31}        1{col 42}      1.8{col 53}       53
{col 8}{res}cd_merge{col 17}{txt}{c |}{res}{col 21}   1,796{col 31}        1{col 42}      1.0{col 53}        2
{txt}{hline 16}{c BT}{hline 44}

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}    16.56
{txt}Log likelihood = {res}-1312.9232{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.1670
{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              outsource{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}auto_fbavg {c |}{col 25}{res}{space 2} .1983871{col 37}{space 2} .1920175{col 48}{space 1}    1.03{col 57}{space 3}0.302{col 65}{space 4}-.1779604{col 78}{space 3} .5747345
{txt}{space 11}auto_onetavg {c |}{col 25}{res}{space 2} .2397551{col 37}{space 2} .5827302{col 48}{space 1}    0.41{col 57}{space 3}0.681{col 65}{space 4}-.9023751{col 78}{space 3} 1.381885
{txt}{space 11}offshore_avg {c |}{col 25}{res}{space 2} .0576057{col 37}{space 2} .0528786{col 48}{space 1}    1.09{col 57}{space 3}0.276{col 65}{space 4}-.0460344{col 78}{space 3} .1612458
{txt}{space 13}imppen2012 {c |}{col 25}{res}{space 2}-.0043997{col 37}{space 2} .2345909{col 48}{space 1}   -0.02{col 57}{space 3}0.985{col 65}{space 4}-.4641894{col 78}{space 3}   .45539
{txt}{space 10}foreignbornpc {c |}{col 25}{res}{space 2}-.0143684{col 37}{space 2} .0061663{col 48}{space 1}   -2.33{col 57}{space 3}0.020{col 65}{space 4}-.0264541{col 78}{space 3}-.0022827
{txt}{space 17}gender {c |}{col 25}{res}{space 2}-.0993405{col 37}{space 2}  .121868{col 48}{space 1}   -0.82{col 57}{space 3}0.415{col 65}{space 4}-.3381974{col 78}{space 3} .1395163
{txt}{space 16}partyid {c |}{col 25}{res}{space 2} .0684208{col 37}{space 2}  .032641{col 48}{space 1}    2.10{col 57}{space 3}0.036{col 65}{space 4} .0044457{col 78}{space 3} .1323959
{txt}{space 20}age {c |}{col 25}{res}{space 2}  .015715{col 37}{space 2} .0053327{col 48}{space 1}    2.95{col 57}{space 3}0.003{col 65}{space 4} .0052631{col 78}{space 3} .0261669
{txt}{space 20}edu {c |}{col 25}{res}{space 2} .0083722{col 37}{space 2}  .031923{col 48}{space 1}    0.26{col 57}{space 3}0.793{col 65}{space 4}-.0541957{col 78}{space 3} .0709402
{txt}{space 12}nationalism {c |}{col 25}{res}{space 2} -.035284{col 37}{space 2} .0542709{col 48}{space 1}   -0.65{col 57}{space 3}0.516{col 65}{space 4}-.1416529{col 78}{space 3}  .071085
{txt}{space 8}ethnocentric100 {c |}{col 25}{res}{space 2}-.0892084{col 37}{space 2} .3211802{col 48}{space 1}   -0.28{col 57}{space 3}0.781{col 65}{space 4}  -.71871{col 78}{space 3} .5402931
{txt}{space 14}famincome {c |}{col 25}{res}{space 2} .0109545{col 37}{space 2} .0086814{col 48}{space 1}    1.26{col 57}{space 3}0.207{col 65}{space 4}-.0060607{col 78}{space 3} .0279698
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/cut1 {c |}{col 25}{res}{space 2}-2.199465{col 37}{space 2} .5501151{col 65}{space 4}-3.277671{col 78}{space 3}-1.121259
{txt}{space 18}/cut2 {c |}{col 25}{res}{space 2} .2401611{col 37}{space 2} .4527196{col 65}{space 4} -.647153{col 78}{space 3} 1.127475
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet                {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .1267808{col 37}{space 2} .1078925{col 65}{space 4} .0239148{col 78}{space 3} .6721089
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry       {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} 1.33e-32{col 37}{space 2} 2.56e-17{col 65}{space 4}        .{col 78}{space 3}        .
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}cc_onet>industry>      {col 25}{txt}{c |}
{col 1}{res}cd_merge               {col 25}{txt}{c |}
{space 14}var(_cons){c |}{col 25}{res}{space 2} .4770915{col 37}{space 2} 1.365852{col 65}{space 4} .0017447{col 78}{space 3} 130.4614
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}chi2({res}2{txt}) ={res} 2.88{col 59}{txt}Prob > chi2 ={res}{col 73}0.2366

{txt}{p 0 6 4 79}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}
({res}est10{txt} stored)

{com}. esttab using mainresults.tex, b(2) se(2) label replace booktabs alignment(D{c -(}.{c )-}{c -(}.{c )-}{c -(}-1{c )-}) title(Regression table\label{c -(}tab1{c )-}) page(dcolumn) nonumber 
{res}{txt}(note: file mainresults.tex not found)
(output written to {browse  `"mainresults.tex"'})

{com}. 
. ologit immglevel3 auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1858.3799}  
Iteration 1:{space 3}log likelihood = {res:-1633.5758}  
Iteration 2:{space 3}log likelihood = {res:-1628.9353}  
Iteration 3:{space 3}log likelihood = {res:-1628.9303}  
Iteration 4:{space 3}log likelihood = {res:-1628.9303}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,811
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}    458.90
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1628.9303{txt}{col 49}Pseudo R2{col 67}= {res}    0.1235

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      immglevel3{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .4053629{col 30}{space 2} .1425561{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .1259581{col 71}{space 3} .6847677
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .3464275{col 30}{space 2} .4392328{col 41}{space 1}    0.79{col 50}{space 3}0.430{col 58}{space 4} -.514453{col 71}{space 3} 1.207308
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2}-.0200685{col 30}{space 2} .0385022{col 41}{space 1}   -0.52{col 50}{space 3}0.602{col 58}{space 4}-.0955315{col 71}{space 3} .0553945
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.1572295{col 30}{space 2}  .178985{col 41}{space 1}   -0.88{col 50}{space 3}0.380{col 58}{space 4}-.5080336{col 71}{space 3} .1935746
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.719306{col 30}{space 2} .4771958{col 41}{space 1}   -3.60{col 50}{space 3}0.000{col 58}{space 4}-2.654593{col 71}{space 3}-.7840199
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.2496556{col 30}{space 2} .0964811{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4} -.438755{col 71}{space 3}-.0605561
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .2894288{col 30}{space 2} .0240898{col 41}{space 1}   12.01{col 50}{space 3}0.000{col 58}{space 4} .2422137{col 71}{space 3} .3366439
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0136527{col 30}{space 2} .0034903{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0068119{col 71}{space 3} .0204936
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.1040757{col 30}{space 2} .0250993{col 41}{space 1}   -4.15{col 50}{space 3}0.000{col 58}{space 4}-.1532693{col 71}{space 3} -.054882
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .2424765{col 30}{space 2}   .04377{col 41}{space 1}    5.54{col 50}{space 3}0.000{col 58}{space 4}  .156689{col 71}{space 3} .3282641
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} 2.356953{col 30}{space 2} .2892408{col 41}{space 1}    8.15{col 50}{space 3}0.000{col 58}{space 4} 1.790051{col 71}{space 3} 2.923854
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0101116{col 30}{space 2} .0069515{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0035131{col 71}{space 3} .0237362
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-.7489252{col 30}{space 2} .3554004{col 58}{space 4}-1.445497{col 71}{space 3}-.0523532
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} 1.654863{col 30}{space 2} .3564547{col 58}{space 4} .9562243{col 71}{space 3} 2.353501
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,811
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(immglevel3==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .0796772{col 30}{space 2} .0278445{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0251031{col 71}{space 3} .1342513
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}  .068093{col 30}{space 2} .0863173{col 41}{space 1}    0.79{col 50}{space 3}0.430{col 58}{space 4}-.1010859{col 71}{space 3} .2372718
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2}-.0039446{col 30}{space 2} .0075666{col 41}{space 1}   -0.52{col 50}{space 3}0.602{col 58}{space 4}-.0187749{col 71}{space 3} .0108857
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0309047{col 30}{space 2} .0351554{col 41}{space 1}   -0.88{col 50}{space 3}0.379{col 58}{space 4} -.099808{col 71}{space 3} .0379987
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.3379429{col 30}{space 2} .0931153{col 41}{space 1}   -3.63{col 50}{space 3}0.000{col 58}{space 4}-.5204456{col 71}{space 3}-.1554402
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0490717{col 30}{space 2} .0188773{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.0860706{col 71}{space 3}-.0120729
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0568894{col 30}{space 2} .0041918{col 41}{space 1}   13.57{col 50}{space 3}0.000{col 58}{space 4} .0486737{col 71}{space 3} .0651052
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0026836{col 30}{space 2} .0006779{col 41}{space 1}    3.96{col 50}{space 3}0.000{col 58}{space 4} .0013548{col 71}{space 3} .0040123
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0204569{col 30}{space 2} .0048817{col 41}{space 1}   -4.19{col 50}{space 3}0.000{col 58}{space 4}-.0300249{col 71}{space 3}-.0108888
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0476606{col 30}{space 2} .0084132{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4} .0311711{col 71}{space 3} .0641502
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} .4632771{col 30}{space 2} .0545993{col 41}{space 1}    8.49{col 50}{space 3}0.000{col 58}{space 4} .3562645{col 71}{space 3} .5702898
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0019875{col 30}{space 2}  .001364{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0006859{col 71}{space 3} .0046609
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store A

. ologit opposetrade3 auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1891.1362}  
Iteration 1:{space 3}log likelihood = {res:-1823.4465}  
Iteration 2:{space 3}log likelihood = {res: -1823.177}  
Iteration 3:{space 3}log likelihood = {res:-1823.1769}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,801
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}    135.92
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1823.1769{txt}{col 49}Pseudo R2{col 67}= {res}    0.0359

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    opposetrade3{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .3266172{col 30}{space 2} .1367624{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0585678{col 71}{space 3} .5946666
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}-.6896712{col 30}{space 2} .4213719{col 41}{space 1}   -1.64{col 50}{space 3}0.102{col 58}{space 4}-1.515545{col 71}{space 3} .1362027
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2} .0630169{col 30}{space 2} .0375779{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0106344{col 71}{space 3} .1366682
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.2698803{col 30}{space 2} .2151765{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.6916184{col 71}{space 3} .1518579
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.166249{col 30}{space 2} .4679334{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-2.083382{col 71}{space 3}-.2491167
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.1782464{col 30}{space 2}  .092237{col 41}{space 1}   -1.93{col 50}{space 3}0.053{col 58}{space 4}-.3590275{col 71}{space 3} .0025347
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .1177606{col 30}{space 2} .0224939{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0736733{col 71}{space 3} .1618479
{txt}{space 13}age {c |}{col 18}{res}{space 2} -.006881{col 30}{space 2} .0033231{col 41}{space 1}   -2.07{col 50}{space 3}0.038{col 58}{space 4}-.0133942{col 71}{space 3}-.0003678
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.1320386{col 30}{space 2} .0241349{col 41}{space 1}   -5.47{col 50}{space 3}0.000{col 58}{space 4}-.1793421{col 71}{space 3} -.084735
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0483687{col 30}{space 2} .0424766{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0348839{col 71}{space 3} .1316213
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} .2912934{col 30}{space 2} .2517612{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.2021496{col 71}{space 3} .7847363
{txt}{space 7}famincome {c |}{col 18}{res}{space 2}-.0088104{col 30}{space 2} .0066149{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.0217754{col 71}{space 3} .0041545
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.982172{col 30}{space 2} .3420621{col 58}{space 4}-2.652601{col 71}{space 3}-1.311742
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2}-.0393959{col 30}{space 2} .3387884{col 58}{space 4}-.7034089{col 71}{space 3} .6246171
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,801
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(opposetrade3==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .0486315{col 30}{space 2} .0203834{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0086808{col 71}{space 3} .0885822
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}-.1026882{col 30}{space 2} .0627269{col 41}{space 1}   -1.64{col 50}{space 3}0.102{col 58}{space 4}-.2256306{col 71}{space 3} .0202542
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2} .0093829{col 30}{space 2} .0055952{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0015836{col 71}{space 3} .0203493
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0401837{col 30}{space 2} .0320554{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4} -.103011{col 71}{space 3} .0226437
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.1736481{col 30}{space 2} .0698105{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.3104741{col 71}{space 3} -.036822
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0265399{col 30}{space 2} .0137204{col 41}{space 1}   -1.93{col 50}{space 3}0.053{col 58}{space 4}-.0534313{col 71}{space 3} .0003515
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0175339{col 30}{space 2} .0033712{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .0109265{col 71}{space 3} .0241413
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0010245{col 30}{space 2} .0004948{col 41}{space 1}   -2.07{col 50}{space 3}0.038{col 58}{space 4}-.0019943{col 71}{space 3}-.0000548
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0196598{col 30}{space 2} .0036035{col 41}{space 1}   -5.46{col 50}{space 3}0.000{col 58}{space 4}-.0267226{col 71}{space 3} -.012597
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0072018{col 30}{space 2} .0063262{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0051973{col 71}{space 3}  .019601
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2}  .043372{col 30}{space 2} .0374835{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.0300944{col 71}{space 3} .1168383
{txt}{space 7}famincome {c |}{col 18}{res}{space 2}-.0013118{col 30}{space 2} .0009854{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.0032432{col 71}{space 3} .0006195
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store B

. ologit outsource2 auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1334.3362}  
Iteration 1:{space 3}log likelihood = {res: -1314.483}  
Iteration 2:{space 3}log likelihood = {res:-1314.3647}  
Iteration 3:{space 3}log likelihood = {res:-1314.3647}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,814
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     39.94
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0001
{txt}Log likelihood = {res}-1314.3647{txt}{col 49}Pseudo R2{col 67}= {res}    0.0150

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      outsource2{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .2237689{col 30}{space 2} .1578818{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0856737{col 71}{space 3} .5332114
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .0771431{col 30}{space 2} .4823826{col 41}{space 1}    0.16{col 50}{space 3}0.873{col 58}{space 4}-.8683095{col 71}{space 3} 1.022596
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2} .0569394{col 30}{space 2} .0437074{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4}-.0287255{col 71}{space 3} .1426044
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0498555{col 30}{space 2} .2053876{col 41}{space 1}   -0.24{col 50}{space 3}0.808{col 58}{space 4}-.4524077{col 71}{space 3} .3526967
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.329253{col 30}{space 2} .5145608{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-2.337774{col 71}{space 3}-.3207325
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.1209593{col 30}{space 2} .1058636{col 41}{space 1}   -1.14{col 50}{space 3}0.253{col 58}{space 4}-.3284481{col 71}{space 3} .0865295
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0594456{col 30}{space 2} .0258378{col 41}{space 1}    2.30{col 50}{space 3}0.021{col 58}{space 4} .0088043{col 71}{space 3} .1100868
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0138913{col 30}{space 2} .0038549{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0063358{col 71}{space 3} .0214467
{txt}{space 13}edu {c |}{col 18}{res}{space 2} .0017336{col 30}{space 2} .0274364{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.0520407{col 71}{space 3} .0555079
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}-.0340673{col 30}{space 2} .0479115{col 41}{space 1}   -0.71{col 50}{space 3}0.477{col 58}{space 4}-.1279721{col 71}{space 3} .0598375
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2}-.0722237{col 30}{space 2} .2845911{col 41}{space 1}   -0.25{col 50}{space 3}0.800{col 58}{space 4}-.6300119{col 71}{space 3} .4855646
{txt}{space 7}famincome {c |}{col 18}{res}{space 2}  .010394{col 30}{space 2} .0074823{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4} -.004271{col 71}{space 3}  .025059
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-2.172183{col 30}{space 2} .4003692{col 58}{space 4}-2.956892{col 71}{space 3}-1.387473
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} .1010414{col 30}{space 2} .3893395{col 58}{space 4}-.6620499{col 71}{space 3} .8641327
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,814
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(outsource2==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg offshore_avg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .0460139{col 30}{space 2} .0324058{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0175004{col 71}{space 3} .1095281
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}  .015863{col 30}{space 2} .0991897{col 41}{space 1}    0.16{col 50}{space 3}0.873{col 58}{space 4}-.1785452{col 71}{space 3} .2102713
{txt}{space 4}offshore_avg {c |}{col 18}{res}{space 2} .0117085{col 30}{space 2} .0089751{col 41}{space 1}    1.30{col 50}{space 3}0.192{col 58}{space 4}-.0058823{col 71}{space 3} .0292994
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0102519{col 30}{space 2} .0422309{col 41}{space 1}   -0.24{col 50}{space 3}0.808{col 58}{space 4}-.0930229{col 71}{space 3} .0725192
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2} -.273336{col 30}{space 2} .1051289{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.4793848{col 71}{space 3}-.0672872
{txt}{space 10}gender {c |}{col 18}{res}{space 2} -.024873{col 30}{space 2} .0217424{col 41}{space 1}   -1.14{col 50}{space 3}0.253{col 58}{space 4}-.0674873{col 71}{space 3} .0177413
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0122239{col 30}{space 2} .0052893{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0018569{col 71}{space 3} .0225908
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0028565{col 30}{space 2} .0007836{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .0013206{col 71}{space 3} .0043923
{txt}{space 13}edu {c |}{col 18}{res}{space 2} .0003565{col 30}{space 2} .0056419{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.0107014{col 71}{space 3} .0114143
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}-.0070053{col 30}{space 2} .0098486{col 41}{space 1}   -0.71{col 50}{space 3}0.477{col 58}{space 4}-.0263082{col 71}{space 3} .0122976
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2}-.0148514{col 30}{space 2} .0585184{col 41}{space 1}   -0.25{col 50}{space 3}0.800{col 58}{space 4}-.1295453{col 71}{space 3} .0998424
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0021373{col 30}{space 2} .0015359{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.0008729{col 71}{space 3} .0051476
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store C

. 
. coefplot (A, label(Fewer immigrants)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Fewer immigrants)
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/A.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/A.gph saved)

{com}. coefplot (B, label(Oppose trade) msymbol(T)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Oppose trade)
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/B.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/B.gph saved)

{com}. coefplot (C, label(Discourage offshoring) msymbol(S)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Discourage offshoring) 
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/C.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/C.gph saved)

{com}. graph combine "/Users/nicolewu/Desktop/Automation/A.gph" "/Users/nicolewu/Desktop/Automation/B.gph" "/Users/nicolewu/Desktop/Automation/C.gph"
{res}
{com}. 
. eststo clear

. eststo: ologit opposetrade auto_onetavg foreignbornpc100 gender partyid age edu nationalism ethnocentric100 if laborforce == 0 | unemployed == 1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1653.7276}  
Iteration 1:{space 3}log likelihood = {res:-1608.0616}  
Iteration 2:{space 3}log likelihood = {res:-1607.7394}  
Iteration 3:{space 3}log likelihood = {res:-1607.7393}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       987
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     91.98
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1607.7393{txt}{col 49}Pseudo R2{col 67}= {res}    0.0278

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     opposetrade{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}auto_onetavg {c |}{col 18}{res}{space 2} 1.084142{col 30}{space 2} .4962831{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .1114454{col 71}{space 3} 2.056839
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-3.026156{col 30}{space 2} .6398695{col 41}{space 1}   -4.73{col 50}{space 3}0.000{col 58}{space 4}-4.280278{col 71}{space 3}-1.772035
{txt}{space 10}gender {c |}{col 18}{res}{space 2} -.199873{col 30}{space 2}  .117312{col 41}{space 1}   -1.70{col 50}{space 3}0.088{col 58}{space 4}-.4298002{col 71}{space 3} .0300542
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .1006534{col 30}{space 2} .0273608{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0470271{col 71}{space 3} .1542796
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0073101{col 30}{space 2} .0033047{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.0137873{col 71}{space 3} -.000833
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.1229517{col 30}{space 2} .0259217{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4}-.1737572{col 71}{space 3}-.0721462
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0809778{col 30}{space 2} .0534279{col 41}{space 1}    1.52{col 50}{space 3}0.130{col 58}{space 4}-.0237389{col 71}{space 3} .1856944
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2}-.0453702{col 30}{space 2} .3488965{col 41}{space 1}   -0.13{col 50}{space 3}0.897{col 58}{space 4}-.7291947{col 71}{space 3} .6384544
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-3.559706{col 30}{space 2} .4028227{col 58}{space 4}-4.349223{col 71}{space 3}-2.770188
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2}-1.976336{col 30}{space 2} .3898986{col 58}{space 4}-2.740523{col 71}{space 3}-1.212149
{txt}{space 11}/cut3 {c |}{col 18}{res}{space 2}-1.767922{col 30}{space 2} .3888689{col 58}{space 4}-2.530091{col 71}{space 3}-1.005753
{txt}{space 11}/cut4 {c |}{col 18}{res}{space 2}  -.07571{col 30}{space 2} .3848593{col 58}{space 4}-.8300204{col 71}{space 3} .6786005
{txt}{space 11}/cut5 {c |}{col 18}{res}{space 2} .1627701{col 30}{space 2} .3856887{col 58}{space 4}-.5931658{col 71}{space 3}  .918706
{txt}{space 11}/cut6 {c |}{col 18}{res}{space 2} 1.052016{col 30}{space 2}  .392613{col 58}{space 4} .2825086{col 71}{space 3} 1.821523
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est1{txt} stored)

{com}. eststo: ologit immglevel auto_onetavg foreignbornpc100 gender partyid age edu nationalism ethnocentric100 if laborforce == 0 | unemployed == 1

{res}{txt}Iteration 0:{space 3}log likelihood = {res: -1410.502}  
Iteration 1:{space 3}log likelihood = {res: -1260.133}  
Iteration 2:{space 3}log likelihood = {res:-1256.8434}  
Iteration 3:{space 3}log likelihood = {res:-1256.8393}  
Iteration 4:{space 3}log likelihood = {res:-1256.8393}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       995
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}    307.33
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1256.8393{txt}{col 49}Pseudo R2{col 67}= {res}    0.1089

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       immglevel{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}auto_onetavg {c |}{col 18}{res}{space 2} 1.388899{col 30}{space 2} .5237636{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .3623414{col 71}{space 3} 2.415457
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-2.379939{col 30}{space 2} .6595467{col 41}{space 1}   -3.61{col 50}{space 3}0.000{col 58}{space 4}-3.672627{col 71}{space 3}-1.087251
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.1149206{col 30}{space 2}  .120689{col 41}{space 1}   -0.95{col 50}{space 3}0.341{col 58}{space 4}-.3514666{col 71}{space 3} .1216254
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .3227033{col 30}{space 2} .0293119{col 41}{space 1}   11.01{col 50}{space 3}0.000{col 58}{space 4}  .265253{col 71}{space 3} .3801536
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0088398{col 30}{space 2}  .003457{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4} .0020642{col 71}{space 3} .0156155
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0940507{col 30}{space 2} .0269415{col 41}{space 1}   -3.49{col 50}{space 3}0.000{col 58}{space 4} -.146855{col 71}{space 3}-.0412464
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}  .196964{col 30}{space 2} .0557053{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0877836{col 71}{space 3} .3061443
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} 2.823586{col 30}{space 2} .3769935{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} 2.084693{col 71}{space 3}  3.56248
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.957554{col 30}{space 2}  .419523{col 58}{space 4}-2.779804{col 71}{space 3}-1.135304
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2}-.7097935{col 30}{space 2}   .40492{col 58}{space 4}-1.503422{col 71}{space 3} .0838351
{txt}{space 11}/cut3 {c |}{col 18}{res}{space 2} 1.546346{col 30}{space 2} .4047923{col 58}{space 4} .7529677{col 71}{space 3} 2.339724
{txt}{space 11}/cut4 {c |}{col 18}{res}{space 2} 2.555313{col 30}{space 2} .4098745{col 58}{space 4} 1.751973{col 71}{space 3} 3.358652
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est2{txt} stored)

{com}. eststo: ologit outsource auto_onetavg foreignbornpc100 gender partyid age edu nationalism ethnocentric100 if laborforce == 0 | unemployed == 1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-747.43914}  
Iteration 1:{space 3}log likelihood = {res:-742.75042}  
Iteration 2:{space 3}log likelihood = {res:-742.73958}  
Iteration 3:{space 3}log likelihood = {res:-742.73957}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       993
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}      9.40
{txt}{col 49}Prob > chi2{col 67}= {res}    0.3098
{txt}Log likelihood = {res}-742.73957{txt}{col 49}Pseudo R2{col 67}= {res}    0.0063

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       outsource{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}auto_onetavg {c |}{col 18}{res}{space 2}-.1544951{col 30}{space 2} .5908424{col 41}{space 1}   -0.26{col 50}{space 3}0.794{col 58}{space 4}-1.312525{col 71}{space 3} 1.003535
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.8983758{col 30}{space 2} .7356665{col 41}{space 1}   -1.22{col 50}{space 3}0.222{col 58}{space 4}-2.340256{col 71}{space 3}  .543504
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.2328124{col 30}{space 2} .1380236{col 41}{space 1}   -1.69{col 50}{space 3}0.092{col 58}{space 4}-.5033337{col 71}{space 3}  .037709
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0051245{col 30}{space 2} .0319592{col 41}{space 1}    0.16{col 50}{space 3}0.873{col 58}{space 4}-.0575145{col 71}{space 3} .0677634
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0066072{col 30}{space 2}  .003894{col 41}{space 1}    1.70{col 50}{space 3}0.090{col 58}{space 4}-.0010248{col 71}{space 3} .0142393
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0166879{col 30}{space 2} .0301518{col 41}{space 1}   -0.55{col 50}{space 3}0.580{col 58}{space 4}-.0757843{col 71}{space 3} .0424085
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0335153{col 30}{space 2} .0620275{col 41}{space 1}    0.54{col 50}{space 3}0.589{col 58}{space 4}-.0880564{col 71}{space 3} .1550869
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} -.334583{col 30}{space 2} .4044601{col 41}{space 1}   -0.83{col 50}{space 3}0.408{col 58}{space 4} -1.12731{col 71}{space 3} .4581443
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-2.994687{col 30}{space 2} .4711428{col 58}{space 4} -3.91811{col 71}{space 3}-2.071264
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2}-.7745614{col 30}{space 2} .4520902{col 58}{space 4}-1.660642{col 71}{space 3} .1115191
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est3{txt} stored)

{com}. esttab using displaced.tex, b(2) se(2) label replace booktabs alignment(D{c -(}.{c )-}{c -(}.{c )-}{c -(}-1{c )-}) title(Regression table\label{c -(}tab1{c )-}) page(dcolumn) nonumber 
{res}{txt}(output written to {browse  `"displaced.tex"'})

{com}. 
. eststo clear

. eststo: ologit immglevel auto_fbavg auto_onetavg if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1826.7615}  
Iteration 1:{space 3}log likelihood = {res: -1815.505}  
Iteration 2:{space 3}log likelihood = {res:-1815.4889}  
Iteration 3:{space 3}log likelihood = {res:-1815.4889}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,294
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}     22.55
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1815.4889{txt}{col 49}Pseudo R2{col 67}= {res}    0.0062

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   immglevel{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}auto_fbavg {c |}{col 14}{res}{space 2} .6004248{col 26}{space 2} .1391989{col 37}{space 1}    4.31{col 46}{space 3}0.000{col 54}{space 4}    .3276{col 67}{space 3} .8732497
{txt}auto_onetavg {c |}{col 14}{res}{space 2} .5670981{col 26}{space 2} .4766749{col 37}{space 1}    1.19{col 46}{space 3}0.234{col 54}{space 4}-.3671676{col 67}{space 3} 1.501364
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}  -2.3692{col 26}{space 2} .1737752{col 54}{space 4}-2.709793{col 67}{space 3}-2.028607
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2}-1.261582{col 26}{space 2} .1493169{col 54}{space 4}-1.554237{col 67}{space 3}-.9689257
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} .7775448{col 26}{space 2} .1458167{col 54}{space 4} .4917493{col 67}{space 3}  1.06334
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.751185{col 26}{space 2} .1523154{col 54}{space 4} 1.452652{col 67}{space 3} 2.049718
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est1{txt} stored)

{com}. eststo: ologit immglevel auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1590.1736}  
Iteration 1:{space 3}log likelihood = {res:-1454.7014}  
Iteration 2:{space 3}log likelihood = {res:-1451.7212}  
Iteration 3:{space 3}log likelihood = {res:-1451.7128}  
Iteration 4:{space 3}log likelihood = {res:-1451.7128}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,124
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}    276.92
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1451.7128{txt}{col 49}Pseudo R2{col 67}= {res}    0.0871

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       immglevel{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .4981012{col 30}{space 2} .1706009{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .1637296{col 71}{space 3} .8324729
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .2134639{col 30}{space 2} .5216295{col 41}{space 1}    0.41{col 50}{space 3}0.682{col 58}{space 4} -.808911{col 71}{space 3} 1.235839
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0325437{col 30}{space 2} .2128229{col 41}{space 1}   -0.15{col 50}{space 3}0.878{col 58}{space 4}-.4496689{col 71}{space 3} .3845814
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.428661{col 30}{space 2} .5787224{col 41}{space 1}   -2.47{col 50}{space 3}0.014{col 58}{space 4}-2.562936{col 71}{space 3}-.2943856
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.2016162{col 30}{space 2} .1157642{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.4285099{col 71}{space 3} .0252776
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .2728047{col 30}{space 2} .0292506{col 41}{space 1}    9.33{col 50}{space 3}0.000{col 58}{space 4} .2154746{col 71}{space 3} .3301347
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0138747{col 30}{space 2} .0040238{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0059882{col 71}{space 3} .0217612
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0450052{col 30}{space 2} .0288763{col 41}{space 1}   -1.56{col 50}{space 3}0.119{col 58}{space 4}-.1016017{col 71}{space 3} .0115913
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .2779195{col 30}{space 2} .0530031{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .1740353{col 71}{space 3} .3818038
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} 2.097771{col 30}{space 2} .3310689{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} 1.448888{col 71}{space 3} 2.746654
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0142848{col 30}{space 2} .0083383{col 41}{space 1}    1.71{col 50}{space 3}0.087{col 58}{space 4}-.0020578{col 71}{space 3} .0306275
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.127537{col 30}{space 2} .4397295{col 58}{space 4}-1.989391{col 71}{space 3}-.2656826
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} .0565316{col 30}{space 2} .4289466{col 58}{space 4}-.7841884{col 71}{space 3} .8972516
{txt}{space 11}/cut3 {c |}{col 18}{res}{space 2} 2.413257{col 30}{space 2}  .432236{col 58}{space 4}  1.56609{col 71}{space 3} 3.260424
{txt}{space 11}/cut4 {c |}{col 18}{res}{space 2} 3.557217{col 30}{space 2} .4401262{col 58}{space 4} 2.694585{col 71}{space 3} 4.419848
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est2{txt} stored)

{com}. eststo: ologit opposetrade auto_fbavg auto_onetavg if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-2124.0962}  
Iteration 1:{space 3}log likelihood = {res:-2113.0942}  
Iteration 2:{space 3}log likelihood = {res:-2113.0774}  
Iteration 3:{space 3}log likelihood = {res:-2113.0774}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,290
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}     22.04
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-2113.0774{txt}{col 49}Pseudo R2{col 67}= {res}    0.0052

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} opposetrade{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}auto_fbavg {c |}{col 14}{res}{space 2} .5933441{col 26}{space 2} .1381144{col 37}{space 1}    4.30{col 46}{space 3}0.000{col 54}{space 4} .3226448{col 67}{space 3} .8640434
{txt}auto_onetavg {c |}{col 14}{res}{space 2}-1.270504{col 26}{space 2} .4751207{col 37}{space 1}   -2.67{col 46}{space 3}0.007{col 54}{space 4}-2.201724{col 67}{space 3} -.339285
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-2.373151{col 26}{space 2} .1632142{col 54}{space 4}-2.693045{col 67}{space 3}-2.053257
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2}-.8925898{col 26}{space 2} .1437677{col 54}{space 4}-1.174369{col 67}{space 3}-.6108104
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2}-.5135439{col 26}{space 2} .1423086{col 54}{space 4}-.7924637{col 67}{space 3}-.2346241
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.385779{col 26}{space 2} .1482599{col 54}{space 4} 1.095195{col 67}{space 3} 1.676363
{txt}{space 7}/cut5 {c |}{col 14}{res}{space 2}  1.68788{col 26}{space 2} .1517594{col 54}{space 4} 1.390437{col 67}{space 3} 1.985323
{txt}{space 7}/cut6 {c |}{col 14}{res}{space 2} 2.627767{col 26}{space 2} .1716708{col 54}{space 4} 2.291299{col 67}{space 3} 2.964236
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est3{txt} stored)

{com}. eststo: ologit opposetrade auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1850.2954}  
Iteration 1:{space 3}log likelihood = {res: -1816.107}  
Iteration 2:{space 3}log likelihood = {res:-1815.6814}  
Iteration 3:{space 3}log likelihood = {res: -1815.676}  
Iteration 4:{space 3}log likelihood = {res: -1815.676}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,119
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     69.24
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -1815.676{txt}{col 49}Pseudo R2{col 67}= {res}    0.0187

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     opposetrade{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .3508019{col 30}{space 2} .1659595{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0255273{col 71}{space 3} .6760766
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} -.954611{col 30}{space 2} .5157782{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-1.965518{col 71}{space 3} .0562958
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2} -.273729{col 30}{space 2} .2377752{col 41}{space 1}   -1.15{col 50}{space 3}0.250{col 58}{space 4}-.7397599{col 71}{space 3} .1923019
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.371998{col 30}{space 2} .5767596{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-2.502427{col 71}{space 3}-.2415704
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.1890649{col 30}{space 2}  .112935{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.4104135{col 71}{space 3} .0322836
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .1088038{col 30}{space 2} .0278065{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4}  .054304{col 71}{space 3} .1633035
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0053041{col 30}{space 2} .0039047{col 41}{space 1}   -1.36{col 50}{space 3}0.174{col 58}{space 4}-.0129572{col 71}{space 3} .0023491
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0966521{col 30}{space 2} .0288998{col 41}{space 1}   -3.34{col 50}{space 3}0.001{col 58}{space 4}-.1532946{col 71}{space 3}-.0400096
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0272356{col 30}{space 2}   .05155{col 41}{space 1}    0.53{col 50}{space 3}0.597{col 58}{space 4}-.0738006{col 71}{space 3} .1282718
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2} .3837003{col 30}{space 2} .2997769{col 41}{space 1}    1.28{col 50}{space 3}0.201{col 58}{space 4}-.2038517{col 71}{space 3} .9712522
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0013594{col 30}{space 2} .0080636{col 41}{space 1}    0.17{col 50}{space 3}0.866{col 58}{space 4}-.0144449{col 71}{space 3} .0171637
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}  -3.5484{col 30}{space 2}  .437901{col 58}{space 4} -4.40667{col 71}{space 3} -2.69013
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2}-1.958699{col 30}{space 2} .4254583{col 58}{space 4}-2.792582{col 71}{space 3}-1.124816
{txt}{space 11}/cut3 {c |}{col 18}{res}{space 2}-1.557252{col 30}{space 2}  .423754{col 58}{space 4}-2.387795{col 71}{space 3}-.7267092
{txt}{space 11}/cut4 {c |}{col 18}{res}{space 2} .3580326{col 30}{space 2} .4216772{col 58}{space 4}-.4684395{col 71}{space 3} 1.184505
{txt}{space 11}/cut5 {c |}{col 18}{res}{space 2} .6753342{col 30}{space 2} .4232686{col 58}{space 4}-.1542569{col 71}{space 3} 1.504925
{txt}{space 11}/cut6 {c |}{col 18}{res}{space 2} 1.582931{col 30}{space 2} .4320374{col 58}{space 4} .7361532{col 71}{space 3} 2.429709
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est4{txt} stored)

{com}. eststo: ologit outsource auto_fbavg auto_onetavg if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-982.06082}  
Iteration 1:{space 3}log likelihood = {res:-979.91664}  
Iteration 2:{space 3}log likelihood = {res:-979.91514}  
Iteration 3:{space 3}log likelihood = {res:-979.91514}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,299
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      4.29
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1170
{txt}Log likelihood = {res}-979.91514{txt}{col 49}Pseudo R2{col 67}= {res}    0.0022

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   outsource{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}auto_fbavg {c |}{col 14}{res}{space 2} .2744056{col 26}{space 2} .1619126{col 37}{space 1}    1.69{col 46}{space 3}0.090{col 54}{space 4}-.0429372{col 67}{space 3} .5917484
{txt}auto_onetavg {c |}{col 14}{res}{space 2} .4964569{col 26}{space 2} .5636309{col 37}{space 1}    0.88{col 46}{space 3}0.378{col 54}{space 4}-.6082394{col 67}{space 3} 1.601153
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-2.717558{col 26}{space 2} .1989756{col 54}{space 4}-3.107543{col 67}{space 3}-2.327573
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2} -.525284{col 26}{space 2} .1646103{col 54}{space 4}-.8479143{col 67}{space 3}-.2026536
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est5{txt} stored)

{com}. eststo: ologit outsource auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric100 famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-857.62539}  
Iteration 1:{space 3}log likelihood = {res:-835.02415}  
Iteration 2:{space 3}log likelihood = {res:-834.81012}  
Iteration 3:{space 3}log likelihood = {res:-834.81008}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,127
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     45.63
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-834.81008{txt}{col 49}Pseudo R2{col 67}= {res}    0.0266

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       outsource{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .5465693{col 30}{space 2} .1994389{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .1556761{col 71}{space 3} .9374624
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}  .295902{col 30}{space 2} .6185223{col 41}{space 1}    0.48{col 50}{space 3}0.632{col 58}{space 4}-.9163795{col 71}{space 3} 1.508183
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2} .1144497{col 30}{space 2} .2763107{col 41}{space 1}    0.41{col 50}{space 3}0.679{col 58}{space 4}-.4271093{col 71}{space 3} .6560088
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.772991{col 30}{space 2} .6524727{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-3.051814{col 71}{space 3}-.4941678
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0498124{col 30}{space 2} .1344828{col 41}{space 1}   -0.37{col 50}{space 3}0.711{col 58}{space 4}-.3133938{col 71}{space 3}  .213769
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0907367{col 30}{space 2} .0332734{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4}  .025522{col 71}{space 3} .1559514
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0159992{col 30}{space 2} .0048058{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4}   .00658{col 71}{space 3} .0254183
{txt}{space 13}edu {c |}{col 18}{res}{space 2} .0506043{col 30}{space 2} .0338201{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0156818{col 71}{space 3} .1168905
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}-.0017849{col 30}{space 2} .0597614{col 41}{space 1}   -0.03{col 50}{space 3}0.976{col 58}{space 4}-.1189151{col 71}{space 3} .1153452
{txt}{space 1}ethnocentric100 {c |}{col 18}{res}{space 2}-.1276985{col 30}{space 2} .3532837{col 41}{space 1}   -0.36{col 50}{space 3}0.718{col 58}{space 4}-.8201218{col 71}{space 3} .5647249
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0160168{col 30}{space 2} .0094514{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0025076{col 71}{space 3} .0345411
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.085731{col 30}{space 2}  .512137{col 58}{space 4}-2.089501{col 71}{space 3}-.0819604
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} 1.119258{col 30}{space 2} .5036478{col 58}{space 4} .1321262{col 71}{space 3} 2.106389
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est6{txt} stored)

{com}. esttab using nontradable.tex, b(2) se(2) label replace booktabs alignment(D{c -(}.{c )-}{c -(}.{c )-}{c -(}-1{c )-}) title(Attitudes toward globalization and tech spending, non-tradable sectors\label{c -(}tab1{c )-}) page(dcolumn) nonumber 
{res}{txt}(note: file nontradable.tex not found)
(output written to {browse  `"nontradable.tex"'})

{com}. 
. eststo clear

. ologit immglevel3 auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1144.8737}  
Iteration 1:{space 3}log likelihood = {res: -1021.501}  
Iteration 2:{space 3}log likelihood = {res:-1019.2706}  
Iteration 3:{space 3}log likelihood = {res:-1019.2667}  
Iteration 4:{space 3}log likelihood = {res:-1019.2667}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,124
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}    251.21
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1019.2667{txt}{col 49}Pseudo R2{col 67}= {res}    0.1097

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      immglevel3{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .4681469{col 30}{space 2}  .181363{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .1126819{col 71}{space 3} .8236118
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .5532111{col 30}{space 2} .5564964{col 41}{space 1}    0.99{col 50}{space 3}0.320{col 58}{space 4}-.5375018{col 71}{space 3} 1.643924
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0516757{col 30}{space 2}  .216526{col 41}{space 1}   -0.24{col 50}{space 3}0.811{col 58}{space 4}-.4760589{col 71}{space 3} .3727075
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.401309{col 30}{space 2} .6080148{col 41}{space 1}   -2.30{col 50}{space 3}0.021{col 58}{space 4}-2.592996{col 71}{space 3}-.2096216
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.2634924{col 30}{space 2} .1232379{col 41}{space 1}   -2.14{col 50}{space 3}0.033{col 58}{space 4}-.5050342{col 71}{space 3}-.0219505
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .2774908{col 30}{space 2} .0309225{col 41}{space 1}    8.97{col 50}{space 3}0.000{col 58}{space 4} .2168838{col 71}{space 3} .3380978
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0125141{col 30}{space 2} .0043162{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0040545{col 71}{space 3} .0209737
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0772368{col 30}{space 2} .0310718{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.1381363{col 71}{space 3}-.0163373
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .2665287{col 30}{space 2} .0550518{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .1586293{col 71}{space 3} .3744282
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2} .0193856{col 30}{space 2} .0035281{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .0124707{col 71}{space 3} .0263004
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0178774{col 30}{space 2} .0088154{col 41}{space 1}    2.03{col 50}{space 3}0.043{col 58}{space 4} .0005995{col 71}{space 3} .0351553
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-.2766326{col 30}{space 2} .4612289{col 58}{space 4}-1.180625{col 71}{space 3} .6273594
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} 2.092517{col 30}{space 2} .4642586{col 58}{space 4} 1.182587{col 71}{space 3} 3.002448
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,124
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(immglevel3==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .0946402{col 30}{space 2} .0363307{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0234333{col 71}{space 3} .1658471
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .1118367{col 30}{space 2} .1124133{col 41}{space 1}    0.99{col 50}{space 3}0.320{col 58}{space 4}-.1084894{col 71}{space 3} .3321628
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0104467{col 30}{space 2} .0437675{col 41}{space 1}   -0.24{col 50}{space 3}0.811{col 58}{space 4}-.0962295{col 71}{space 3} .0753361
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.2832874{col 30}{space 2} .1223533{col 41}{space 1}   -2.32{col 50}{space 3}0.021{col 58}{space 4}-.5230954{col 71}{space 3}-.0434794
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0532674{col 30}{space 2} .0247975{col 41}{space 1}   -2.15{col 50}{space 3}0.032{col 58}{space 4}-.1018696{col 71}{space 3}-.0046652
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0560973{col 30}{space 2} .0055774{col 41}{space 1}   10.06{col 50}{space 3}0.000{col 58}{space 4} .0451658{col 71}{space 3} .0670288
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0025298{col 30}{space 2} .0008631{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0008382{col 71}{space 3} .0042215
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0156141{col 30}{space 2} .0062457{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.0278555{col 71}{space 3}-.0033727
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0538812{col 30}{space 2} .0108221{col 41}{space 1}    4.98{col 50}{space 3}0.000{col 58}{space 4} .0326704{col 71}{space 3} .0750921
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2}  .003919{col 30}{space 2} .0006906{col 41}{space 1}    5.67{col 50}{space 3}0.000{col 58}{space 4} .0025653{col 71}{space 3} .0052726
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0036141{col 30}{space 2} .0017733{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0001384{col 71}{space 3} .0070897
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store E

. ologit opposetrade3 auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1177.6205}  
Iteration 1:{space 3}log likelihood = {res:-1147.3963}  
Iteration 2:{space 3}log likelihood = {res:-1147.3121}  
Iteration 3:{space 3}log likelihood = {res:-1147.3121}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,119
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     60.62
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1147.3121{txt}{col 49}Pseudo R2{col 67}= {res}    0.0257

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    opposetrade3{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .3876698{col 30}{space 2} .1730382{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0485212{col 71}{space 3} .7268184
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}-.8344426{col 30}{space 2} .5373056{col 41}{space 1}   -1.55{col 50}{space 3}0.120{col 58}{space 4}-1.887542{col 71}{space 3}  .218657
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.1662848{col 30}{space 2} .2556507{col 41}{space 1}   -0.65{col 50}{space 3}0.515{col 58}{space 4}-.6673509{col 71}{space 3} .3347813
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.9124865{col 30}{space 2} .5966519{col 41}{space 1}   -1.53{col 50}{space 3}0.126{col 58}{space 4}-2.081903{col 71}{space 3} .2569296
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.1189916{col 30}{space 2} .1171991{col 41}{space 1}   -1.02{col 50}{space 3}0.310{col 58}{space 4}-.3486976{col 71}{space 3} .1107143
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .1081792{col 30}{space 2} .0288207{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0516918{col 71}{space 3} .1646667
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0054137{col 30}{space 2} .0040856{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.0134212{col 71}{space 3} .0025939
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0905666{col 30}{space 2} .0301097{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.1495806{col 71}{space 3}-.0315526
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0423507{col 30}{space 2} .0531804{col 41}{space 1}    0.80{col 50}{space 3}0.426{col 58}{space 4} -.061881{col 71}{space 3} .1465825
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2} .0032781{col 30}{space 2} .0031493{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.0028945{col 71}{space 3} .0094506
{txt}{space 7}famincome {c |}{col 18}{res}{space 2}-.0030112{col 30}{space 2} .0083336{col 41}{space 1}   -0.36{col 50}{space 3}0.718{col 58}{space 4}-.0193447{col 71}{space 3} .0133223
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.404286{col 30}{space 2} .4404579{col 58}{space 4}-2.267568{col 71}{space 3}-.5410045
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} .5098223{col 30}{space 2}  .438789{col 58}{space 4}-.3501884{col 71}{space 3} 1.369833
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,119
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(opposetrade3==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .0592414{col 30}{space 2} .0264774{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0073467{col 71}{space 3} .1111361
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}-.1275146{col 30}{space 2} .0821163{col 41}{space 1}   -1.55{col 50}{space 3}0.120{col 58}{space 4}-.2884596{col 71}{space 3} .0334305
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2}-.0254107{col 30}{space 2} .0390759{col 41}{space 1}   -0.65{col 50}{space 3}0.516{col 58}{space 4} -.101998{col 71}{space 3} .0511767
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-.1394408{col 30}{space 2} .0912549{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4}-.3182971{col 71}{space 3} .0394155
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0181836{col 30}{space 2} .0178973{col 41}{space 1}   -1.02{col 50}{space 3}0.310{col 58}{space 4}-.0532617{col 71}{space 3} .0168945
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0165313{col 30}{space 2} .0044299{col 41}{space 1}    3.73{col 50}{space 3}0.000{col 58}{space 4} .0078489{col 71}{space 3} .0252137
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0008273{col 30}{space 2}  .000624{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.0020504{col 71}{space 3} .0003958
{txt}{space 13}edu {c |}{col 18}{res}{space 2}-.0138399{col 30}{space 2} .0046112{col 41}{space 1}   -3.00{col 50}{space 3}0.003{col 58}{space 4}-.0228776{col 71}{space 3}-.0048021
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2} .0064718{col 30}{space 2} .0081269{col 41}{space 1}    0.80{col 50}{space 3}0.426{col 58}{space 4}-.0094567{col 71}{space 3} .0224003
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2} .0005009{col 30}{space 2} .0004814{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.0004425{col 71}{space 3} .0014444
{txt}{space 7}famincome {c |}{col 18}{res}{space 2}-.0004601{col 30}{space 2} .0012735{col 41}{space 1}   -0.36{col 50}{space 3}0.718{col 58}{space 4}-.0029561{col 71}{space 3} .0020358
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store F

. ologit outsource2 auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome if laborforce == 1 & offshore_avg==1

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-857.62539}  
Iteration 1:{space 3}log likelihood = {res:-835.02415}  
Iteration 2:{space 3}log likelihood = {res:-834.81012}  
Iteration 3:{space 3}log likelihood = {res:-834.81008}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     1,127
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     45.63
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-834.81008{txt}{col 49}Pseudo R2{col 67}= {res}    0.0266

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      outsource2{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .5465693{col 30}{space 2} .1994389{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .1556761{col 71}{space 3} .9374624
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2}  .295902{col 30}{space 2} .6185223{col 41}{space 1}    0.48{col 50}{space 3}0.632{col 58}{space 4}-.9163795{col 71}{space 3} 1.508183
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2} .1144497{col 30}{space 2} .2763107{col 41}{space 1}    0.41{col 50}{space 3}0.679{col 58}{space 4}-.4271093{col 71}{space 3} .6560088
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2}-1.772991{col 30}{space 2} .6524727{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-3.051814{col 71}{space 3}-.4941678
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0498124{col 30}{space 2} .1344828{col 41}{space 1}   -0.37{col 50}{space 3}0.711{col 58}{space 4}-.3133938{col 71}{space 3}  .213769
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0907367{col 30}{space 2} .0332734{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4}  .025522{col 71}{space 3} .1559514
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0159992{col 30}{space 2} .0048058{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4}   .00658{col 71}{space 3} .0254183
{txt}{space 13}edu {c |}{col 18}{res}{space 2} .0506043{col 30}{space 2} .0338201{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0156818{col 71}{space 3} .1168905
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}-.0017849{col 30}{space 2} .0597614{col 41}{space 1}   -0.03{col 50}{space 3}0.976{col 58}{space 4}-.1189151{col 71}{space 3} .1153452
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2} -.001277{col 30}{space 2} .0035328{col 41}{space 1}   -0.36{col 50}{space 3}0.718{col 58}{space 4}-.0082012{col 71}{space 3} .0056472
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0160168{col 30}{space 2} .0094514{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0025076{col 71}{space 3} .0345411
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}/cut1 {c |}{col 18}{res}{space 2}-1.085731{col 30}{space 2}  .512137{col 58}{space 4}-2.089501{col 71}{space 3}-.0819604
{txt}{space 11}/cut2 {c |}{col 18}{res}{space 2} 1.119258{col 30}{space 2} .5036478{col 58}{space 4} .1321262{col 71}{space 3} 2.106389
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome) predict(outcome(2)) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,127
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(outsource2==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:auto_fbavg auto_onetavg imppen2012 foreignbornpc100 gender partyid age edu nationalism ethnocentric famincome}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}auto_fbavg {c |}{col 18}{res}{space 2} .1130751{col 30}{space 2} .0408016{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0331053{col 71}{space 3} .1930448
{txt}{space 4}auto_onetavg {c |}{col 18}{res}{space 2} .0612167{col 30}{space 2} .1279106{col 41}{space 1}    0.48{col 50}{space 3}0.632{col 58}{space 4}-.1894835{col 71}{space 3} .3119168
{txt}{space 6}imppen2012 {c |}{col 18}{res}{space 2} .0236775{col 30}{space 2}  .057152{col 41}{space 1}    0.41{col 50}{space 3}0.679{col 58}{space 4}-.0883382{col 71}{space 3} .1356933
{txt}foreignbornpc100 {c |}{col 18}{res}{space 2} -.366799{col 30}{space 2} .1334604{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.6283766{col 71}{space 3}-.1052214
{txt}{space 10}gender {c |}{col 18}{res}{space 2}-.0103053{col 30}{space 2} .0278151{col 41}{space 1}   -0.37{col 50}{space 3}0.711{col 58}{space 4}-.0648219{col 71}{space 3} .0442113
{txt}{space 9}partyid {c |}{col 18}{res}{space 2} .0187717{col 30}{space 2} .0068104{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} .0054236{col 71}{space 3} .0321199
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0033099{col 30}{space 2} .0009778{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .0013935{col 71}{space 3} .0052264
{txt}{space 13}edu {c |}{col 18}{res}{space 2} .0104691{col 30}{space 2} .0069752{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0032021{col 71}{space 3} .0241403
{txt}{space 5}nationalism {c |}{col 18}{res}{space 2}-.0003693{col 30}{space 2} .0123636{col 41}{space 1}   -0.03{col 50}{space 3}0.976{col 58}{space 4}-.0246014{col 71}{space 3} .0238629
{txt}{space 4}ethnocentric {c |}{col 18}{res}{space 2}-.0002642{col 30}{space 2} .0007308{col 41}{space 1}   -0.36{col 50}{space 3}0.718{col 58}{space 4}-.0016965{col 71}{space 3} .0011681
{txt}{space 7}famincome {c |}{col 18}{res}{space 2} .0033136{col 30}{space 2} .0019475{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0005035{col 71}{space 3} .0071307
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. est store G

. 
. coefplot (A, label(Main sample)) (E, label(Nontradable subsample) msymbol(D)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Fewer immigrants) legend(off)
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/E.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/E.gph saved)

{com}. coefplot (B, label(Main sample)) (F, label(Nontradable subsample) msymbol(D)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Oppose trade) legend(off) yscale(off)
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/F.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/F.gph saved)

{com}. coefplot (C, label(Main sample)) (G, label(Nontradable subsample) msymbol(D)), drop(_cons imppen2012 famincome offshore_avg) xline(0) levels(95) xtitle(Average Marginal Effects - Discourage offshoring) legend(off)
{res}
{com}. graph save Graph "/Users/nicolewu/Desktop/Automation/G.gph", replace
{res}{txt}(file /Users/nicolewu/Desktop/Automation/G.gph saved)

{com}. graph combine "/Users/nicolewu/Desktop/Automation/E.gph" "/Users/nicolewu/Desktop/Automation/F.gph" "/Users/nicolewu/Desktop/Automation/G.gph", cols(2) ycommon xcommon iscale(.5) 
{res}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/nicolewu/Desktop/Automation/PSRM Replication/PSRM MB.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}21 Feb 2021, 18:40:30
{txt}{.-}
{smcl}
{txt}{sf}{ul off}